U.S. patent application number 13/371955 was filed with the patent office on 2013-12-26 for detector function and system for predicting airfoil stall from control surface measurements.
This patent application is currently assigned to THE BOARD OF TRUSTEES OF THE UNIVERSITY OF ILLINOIS. The applicant listed for this patent is Phillip J. Ansell, Michael B. Bragg, Michael F. Kerho. Invention is credited to Phillip J. Ansell, Michael B. Bragg, Michael F. Kerho.
Application Number | 20130345910 13/371955 |
Document ID | / |
Family ID | 49775093 |
Filed Date | 2013-12-26 |
United States Patent
Application |
20130345910 |
Kind Code |
A1 |
Kerho; Michael F. ; et
al. |
December 26, 2013 |
DETECTOR FUNCTION AND SYSTEM FOR PREDICTING AIRFOIL STALL FROM
CONTROL SURFACE MEASUREMENTS
Abstract
Methods and apparatus for predicting airfoil stall for an
aircraft having a control surface. Measurements of forces or
moments acting upon an integrated span of the control surface are
sensed over a period of time to provided unsteady data. The
unsteady data is filtered to remove structural frequencies and
input to at least one stall warning detection function, and an
output is received. Each of the stall warning detection functions
identifies an angle-of-attack that is approximately within a
predetermined number of degrees of stall when the received output
reaches a threshold. The received output is compared to the
threshold to determine whether an angle-of-attack exists that is
near stall.
Inventors: |
Kerho; Michael F.; (Thousand
Oaks, CA) ; Bragg; Michael B.; (Champaign, IL)
; Ansell; Phillip J.; (York, PA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Kerho; Michael F.
Bragg; Michael B.
Ansell; Phillip J. |
Thousand Oaks
Champaign
York |
CA
IL
PA |
US
US
US |
|
|
Assignee: |
THE BOARD OF TRUSTEES OF THE
UNIVERSITY OF ILLINOIS
Urbana
IL
|
Family ID: |
49775093 |
Appl. No.: |
13/371955 |
Filed: |
February 13, 2012 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
61442054 |
Feb 11, 2011 |
|
|
|
Current U.S.
Class: |
701/14 |
Current CPC
Class: |
B64D 43/02 20130101 |
Class at
Publication: |
701/14 |
International
Class: |
B64D 43/02 20060101
B64D043/02 |
Goverment Interests
STATEMENT OF GOVERNMENT INTEREST
[0002] This invention was made with Government support under
Contract No. NNX09CF54P awarded by NASA. The Government has certain
rights in the invention.
Claims
1. A method for predicting airfoil stall for an aircraft having a
control surface, the method comprising: measuring forces or moments
acting upon an integrated span of the control surface over a period
of time to provide unsteady data; filtering said unsteady data to
remove structural frequencies and provide filtered unsteady data;
inputting said filtered unsteady data to at least one stall warning
detection function and receiving an output of the at least one
stall warning detection function, each of the at least one stall
warning detection function identifying an angle-of-attack that is
approximately within a predetermined number of degrees of stall
when the received output reaches a threshold; comparing said output
to the threshold to determine whether an angle-of-attack exists
that is near stall.
2. A method for predicting airfoil stall for an aircraft having a
control surface connected to a hinge, the method comprising:
sensing a control surface hinge moment about the hinge over a
period of time; determining unsteady hinge moment data over the
period of time based on said sensed control surface hinge moment;
filtering said determined unsteady hinge moment data to remove
structural frequencies and provide filtered unsteady hinge moment
data; inputting said filtered unsteady hinge moment data to at
least one stall warning detection function and receiving an output
of the at least one stall warning detection function, each of the
at least one stall warning detection function identifying an
angle-of-attack that is approximately within a predetermined number
of degrees of stall when the received output reaches a threshold;
comparing said output to the threshold to determine whether an
angle-of-attack exists that is near stall.
3. The method of claim 2, wherein said filtering comprises
filtering said determined unsteady hinge moment data through a
filter having a band determined based on structural frequencies
capable of influencing hinge moment measurements.
4. The method of claim 2, wherein said determining comprises:
acquiring a plurality of sensed control surface hinge moment
signals over the period of time; and non-dimensionalizing the
plurality of hinge moment signals using data from aircraft sensors
to provide a plurality of unsteady hinge moment coefficients.
5. The method of claim 4 wherein said filtering said determined
unsteady hinge moment data provides a plurality of filtered
unsteady hinge moment coefficients.
6. The method of claim 5, wherein the at least one stall warning
detection function comprises a plurality of stall warning detection
functions; wherein said receiving an output comprises receiving an
output for each of the plurality of stall warning detection
functions and combining the received outputs to provide a combined
output; wherein said comparing said output to the threshold
comprises comparing the combined output to the threshold.
7. The method of claim 6, wherein the plurality of stall warning
detection functions comprise the following, where C.sub.h is the
filtered unsteady hinge moment coefficient, n is a number of
filtered unsteady hinge moment coefficients over the period of time
being considered, and PSD=power spectrum density: Moment = 1 n i =
0 n - 1 ( C h - C _ h ) 4 1 st Function Derivative = 1 n i = 0 n -
1 ( C h 2 t + 2 C h 2 t 2 ) 2 2 nd Function Spectrum = .intg. 0 Hz
50 Hz PSD ( C h ) f 3 rd Function ##EQU00002##
8. The method of claim 7, wherein the plurality of stall warning
detection functions further comprise a function that determines
time normalized energy of the filtered unsteady hinge moment
coefficients.
9. The method of claim 6, wherein said combining the received
outputs comprises averaging the received outputs.
10. The method of claim 6, wherein receiving an output of each of
the plurality of stall warning detection functions comprises:
performing a linear forward wavelet transform on the filtered
unsteady hinge moment coefficient to provide a transformed signal:
performing nonlinear wavelet transform on the transformed signal
using a mother wavelet selected to isolate unsteady separation
content and provide a denoised signal; and performing a linear
inverse wavelet transform on the denoised signal.
11. The method of claim 1, wherein the control surface comprises
one or more of ailerons, rudders, elevators, and flaps of the
aircraft.
12. An apparatus for predicting airfoil stall for an aircraft
control surface, comprising: at least one sensor for sensing a
control surface hinge moment over a period of time; a processor
coupled to said at least one sensor, said processor being
configured to receive the sensed control surface hinge moment over
the period of time from said at least one sensor and determine
whether an angle-of-attack exists that is near stall, said
processor being configured to perform a method comprising:
determining unsteady hinge moment data over the period of time
based on said sensed control surface hinge moment; filtering said
determined unsteady hinge moment data to remove structural
frequencies and provide filtered unsteady hinge moment data;
inputting said filtered unsteady hinge moment data to at least one
stall warning detection function and receiving an output of the at
least one stall warning detection function, each of the at least
one stall warning detection function identifying an angle-of-attack
that is approximately within a predetermined number of degrees of
stall when the received output reaches a threshold; comparing said
output to the threshold to determine whether an angle-of-attack
exists that is near stall.
13. The apparatus of claim 12, wherein said filtering comprises
filtering said determined unsteady hinge moment data through a
filter having a band determined based on structural frequencies
capable of influencing hinge moment measurements.
14. The apparatus of claim 12, wherein said determining comprises:
acquiring a plurality of sensed control surface hinge moment
signals over the period of time; and non-dimensionalizing the
plurality of hinge moment signals using data from aircraft sensors
to provide a plurality of unsteady hinge moment coefficients.
15. The apparatus of claim 14 wherein said filtering said
determined unsteady hinge moment data provides a plurality of
filtered unsteady hinge moment coefficients.
16. The apparatus of claim 15, wherein the at least one stall
warning detection function comprises a plurality of stall warning
detection functions; wherein said receiving an output comprises
receiving an output for each of the plurality of stall warning
detection functions and combining the received outputs to provide a
combined output; wherein said comparing said output to the
threshold comprises comparing the combined output to the
threshold.
17. The apparatus of claim 16, wherein the plurality of stall
warning detection functions comprise the following, where C.sub.h
is the filtered unsteady hinge moment coefficient, n is a number of
filtered unsteady hinge moment coefficients over the period of time
being considered, and PSD=power spectrum density: Moment = 1 n i =
0 n - 1 ( C h - C _ h ) 4 1 st Function Derivative = 1 n i = 0 n -
1 ( C h 2 t + 2 C h 2 t 2 ) 2 2 nd Function Spectrum = .intg. 0 Hz
50 Hz PSD ( C h ) f 3 rd Function ##EQU00003##
18. The apparatus of claim 17, wherein the plurality of stall
warning detection functions further comprise a function that
determines time normalized energy of the filtered unsteady hinge
moment coefficients.
19. The apparatus of claim 16, wherein receiving an output of each
of the plurality of stall warning detection functions comprises:
performing a linear forward wavelet transform on the filtered
unsteady hinge moment coefficient to provide a transformed signal:
performing nonlinear wavelet transform on the transformed signal
using a mother wavelet selected to isolate unsteady separation
content and provide a denoised signal; and performing a linear
inverse wavelet transform on the denoised signal.
20. The apparatus of claim 12, wherein the control surface
comprises one or more of ailerons, rudders, elevators, and flaps of
the aircraft.
21. The apparatus of claim 12, further comprising: a display device
or alarm coupled to said processor for indicating a warning if said
processor determines that the angle-of-attack is near stall.
Description
PRIORITY CLAIM AND REFERENCE TO RELATED APPLICATION
[0001] This application claims the benefit of U.S. Provisional
Application Ser. No. 61/442,054, filed Feb. 11, 2011, under 35
U.S.C. .sctn.119.
FIELD OF THE INVENTION
[0003] A field of the invention is detection functions and systems
for vehicles. Example applications of the invention include
performance and controllability monitoring and stall prediction for
aircraft.
BACKGROUND OF THE INVENTION
[0004] Currently, a problem exists when an aircraft encounters
conditions that could cause contamination on an airfoil. The
airfoil is the two-dimensional cross-section of a wing or tail of
which a control surface, such as a flap, rudder, or elevator, can
be a part. As one example of contamination, an ice shape can form
on the airfoil surface, causing a reduction of lift, increased
drag, and change in quarter-chord pitching and control surface
hinge moments of the airfoil. The presence of the contamination
alters the surface pressure distribution over the airfoil, which
leads to these changes in performance.
[0005] Airfoil surface contamination can also lead to premature
airfoil stall at high angles-of-attack or large flap deflections,
and potentially cause a loss of control of an aircraft. Stall is
caused by the separation of the boundary layer from a surface,
commonly due to an adverse pressure gradient. A
contamination-induced separation can have negative consequences on
the controllability of an aircraft. For example, a premature
airfoil stall may occur as a result of ice accretion, leading to a
reduction of the pressure acting on the upper surface of a control
surface, which imposes an upward unsteady force that acts to
deflect the control surface in that direction. The flap is
essentially sucked upward by the lower pressure, which can lead to
undesirable changes in the aircraft controllability.
[0006] This abrupt contamination-induced flow separation can lead
to a sudden significant change in hinge moment, leaving
insufficient time for a flight crew to react correctly. Such
occurrences have led to aircraft accidents in the past. Therefore,
it is desirable to sense impending problems and to develop systems
to correct or protect against them before an accident becomes
inevitable.
[0007] Another level of protection has been proposed to increase
in-flight pilot awareness by providing information on current and
predicted aircraft performance and controllability, alerting the
flight crew to any aerodynamic degradation of the control
effectiveness due to flowfield separation and unsteadiness. In
addition to flight beyond the baseline, clean-aircraft flight
envelope, such a system will be able to detect a reduction in the
envelope due to several in-flight environmental contaminants such
as heavy rain, in-flight icing encounters, surface contamination in
the form of roughness, and structural damage such as bird strikes
or battle damage.
[0008] Existing systems monitor potential contamination by
measuring surface pressure fluctuations. However, the sensors used
only measure contamination effects at a single point on the
surface.
[0009] U.S. Pat. No. 6,140,942 (incorporated in its entirety herein
by reference) to Bragg et al., discloses an aircraft surface
contamination sensing system and method. The system and method
utilizes a sensor which can be located on or within any control
surface, such as a flap, rudder, or elevator. The sensor senses a
hinge moment over time. The sensor outputs this information to a
processor, which then calculates a control surface hinge moment
coefficient. The control surface steady and/or unsteady hinge
moment coefficients are analyzed, and the control surface hinge
moment coefficient is compared against a clean control surface
value. Once the control surface hinge moment coefficient deviates
from the clean value but before it reaches a critical value, an
appropriate system may be notified. For example, the aircraft
flight crew may be alerted and can modify the flight controls
accordingly. Alternatively, corrective flight systems could be
used.
SUMMARY OF THE INVENTION
[0010] Embodiments of the present invention provide, among other
things, methods and apparatus for predicting airfoil stall for an
aircraft having a control surface. Measurements of forces or
moments acting upon an integrated span of the control surface are
taken over a period of time to provide unsteady data. In some
example embodiments, the measurements are taken by sensing a
control surface hinge moment for a hinge connected to the control
surface. The unsteady data is filtered to remove structural
frequencies. The filtered unsteady data is input to at least one
stall warning detection function, and an output is received. Each
of the stall warning detection functions identifies an
angle-of-attack that is approximately within a predetermined number
of degrees of stall when the received output reaches a threshold.
The received output is compared to the threshold to determine
whether an angle-of-attack exists that is near stall.
BRIEF DESCRIPTION OF THE DRAWINGS
[0011] FIG. 1 is a block diagram of a sensing system constructed in
accordance with embodiments of the present invention;
[0012] FIG. 2 is an isometric cross-sectional view of an aircraft
wing;
[0013] FIG. 3 is a top view of an aircraft wing, illustrating
dimensions used in example calculations;
[0014] FIG. 4 is a flow chart illustrating example methods of the
invention;
[0015] FIG. 5 shows an experimental output of moment, derivative,
and spectrum based detector function outputs for a clean NACA 3415
model as a function of an angle-of-attack, .alpha., at
Re=1.8.times.10.sup.6, and a 0.degree. flap angle;
[0016] FIGS. 6A-6C show an experimental detector threshold boundary
determination for moment function output (FIG. 6A), derivative
function output (FIG. 6B), and spectrum function output (FIG. 6C)
for the clean NACA 3415 model and a model with six simulated
contaminants as a function of an angle-of-attack, .alpha., at
Re=1.8.times.10.sup.6, and a 0.degree. flap setting;
[0017] FIG. 7 shows an experimental effect of flap angle on
detector function threshold level for a warning boundary of
2.degree. for the NACA 3415 model, for Re=1.8.times.10.sup.6;
[0018] FIG. 8 shows an experimental envelope warning prediction
based on developed detector functions for the NACA 3415 clean model
and the model with simulated contaminants as a function of flap
angle, for Re=1.8.times.10.sup.6 and a warning boundary of
2.degree.;
[0019] FIGS. 9A-9C show an example primary (mother) wavelets Sym2
(FIG. 9A), Haar (FIG. 9B), and Coif2 (FIG. 9C) chosen for an
example NACA 23012 analysis;
[0020] FIGS. 10A-10F show experimental unsteady hinge moment signal
denoising and thresholding for warning boundary prediction using
the Haar wavelet for a clean NACA 23012 model at
Re=1.8.times.10.sup.6, and a 0.degree. flap setting, where FIGS.
10A shows a clean lift curve, FIGS. 10B-10E show output from the
Haar based wavelet transform for four selected points,
respectively, and the FIG. 10F shows a percentage of the signal
above the baseline zero value; and
[0021] FIG. 11 shows an example envelope warning prediction based
on the wavelet detector functions for the NACA 23012 clean model
and the model with simulated contaminants, for
Re=1.8.times.10.sup.6, a flap angle of 0.degree., and a warning
boundary of 2.degree..
DETAILED DESCRIPTION
[0022] In embodiments of the present invention a method to analyze
time-dependent data is provided that allows the prediction of
airfoil stall and loss of control without the need to compare to
the clean, not contaminated, airfoil performance. Example systems
can provide envelope protection for the clean airfoil as well as
the airfoil with surface contamination.
[0023] An embodiment of the invention is a detection method and
system used with or as part of an aircraft flight envelope
monitoring system, which in example embodiments provides real-time,
in-cockpit estimations of aircraft flight envelope boundaries,
performance, and controllability. Example embodiments can be
provided as part of an adaptable monitoring system that provides
information on current and predicted aircraft performance and
controllability, alerting a user (e.g., the aircraft's pilot,
flight crew, aircraft automation or other on-board controller,
etc.) to any aerodynamic degradation of the control effectiveness
due to flowfield separation and unsteadiness. In addition to flight
beyond the baseline aircraft flight envelope, example systems can
detect a reduction in the envelope due to various in-flight
environmental contaminants such as heavy rain, in-flight icing
encounters, surface contamination in the form of roughness, and
structural damage such as bird strikes or battle damage, etc. The
example monitoring system is targeted to provide integrated
aerodynamic vehicle health management.
[0024] Embodiments of the present invention provide a system and
method for predicting stall for a vehicle such as an aircraft,
having a control surface, which generally refers to a device for
adjusting aircraft flight attitude (as nonlimiting examples,
ailerons, rudders, elevators, simple flaps, etc.). A sensor or
sensors is provided to take measurements of forces or moments
acting upon an integrated span of the control surface, and a
processor determines unsteady data using these measurements. In
example embodiments, the control surface includes or is connected
to a hinge, or other element capable of being instrumented, by
which fluctuating forces on the aft section of the airfoil can be
measured. The sensing system includes a sensor (or sensors) and a
processor. A display device may also be used to indicate a user
warning It is also contemplated that the processor may output a
signal to a computer-based flight management system through which a
correction or warning could be made.
[0025] The measurements of forces or moments are output to the
processor. For example, if the control surface is connected to a
hinge, the example sensor (or sensors) senses a control surface
hinge moment and outputs this information over time to the
processor. A control surface hinge is used in example embodiments
because it can be easy to instrument and provides an integrated
spanwise measurement. However, example methods of the invention can
be used with similar measurements of force or moment on the control
surface taken elsewhere on the control surface, so long as these
measurements pick up the fluctuations caused by the disturbances in
the flowfield that occur prior to stall.
[0026] An example real-time monitoring system provides unsteady
data by acquiring measurements of the unsteady data, e.g., control
surface hinge moment data, from all aircraft aerodynamic controls.
Time-averaged hinge moments are obtained in particular example
embodiments using (e.g., by calculating the average of) the
unsteady hinge moment measurements. These data are processed, and
information on the current and predicted future state of aircraft
control (including asymmetric cases) is made available to the user.
The use of real-time monitoring of forces or moments acting upon
the integrated span of the control surface, e.g., control surface
hinge moment monitoring, allows an innovative and robust method and
system for predicting aircraft performance and controllability.
Further, as opposed to other, single point sensor monitoring
systems, example systems of the present invention can function by
measuring the integrated effect over the entire control
surface.
[0027] Providing real-time information about the controllability or
loss of lift and reduction of the useable flight envelope is
critical, since loss of control is one of the primary causes of
in-flight accidents. Example hinge moment sensor based aircraft
flight envelope monitoring systems can provide an onboard real-time
assessment of the current state of the aerodynamic health of the
aircraft, alerting the user as controllability boundaries are being
approached while the aircraft is still controllable. Additionally,
example methods and systems can provide a real-time assessment of
the overall change in aircraft performance and controllability due
to both environmental and structural hazards.
[0028] Example systems and methods of the present invention can
employ control surface hinge moment measurements as a system for
sensing aerodynamic lift and/or controllability loss, such as but
not limited to the systems and methods described in U.S. Pat. No.
6,140,942. Such example systems and methods take the hinge moment
data and process the information to provide a reliable and robust
stall prediction function based on the hinge moment results.
Preferred systems and methods can be used to provide an accurate
warning of stall several degrees angle-of-attack prior to actual
stall, alerting the user to the current aircraft envelope
boundaries for both longitudinal and lateral control.
[0029] Turning now to the drawings, FIG. 1 shows a block diagram of
an example system 10. The system 10 includes a sensor or sensors 12
for measuring forces or moments acting upon the integrated span of
the control surface and a processor 14 for analyzing these data.
The sensing system output may be directed to a display or other
output device 16 for displaying a warning should it be needed (or a
current status if no warning is currently needed). Also shown is a
flight control system 18. It is contemplated that the processor 14
could output to the flight control system 18 as an alternative to
or in addition to the display 16. The example sensor 12 may be a
standard strain gauge sensor, which measures the control surface
hinge moment. Other devices capable of detecting the hinge moment,
directly or indirectly, or otherwise capable of measuring forces or
moments acting upon the integrated span of the control surface are
also suitable. The sensor 12 may be mounted within the control
surface to protect it from the environment and minimize its effect
on the wing surface flowfield.
[0030] Referring to FIG. 2, the function of the sensor system 10
will now be described with respect to an aircraft, generally
labeled 20. In particular example systems and methods described
with respect to FIGS. 2-4, the sensor 12 measures forces or moments
acting upon the integrated span of the control surface by measuring
a control surface hinge moment for a hinge connected to the control
surface. The example sensor system 10 is for use on an aircraft 20
of standard design, for instance, having a hinged control surface
such as a flap. In FIG. 2, a wing 22 with a control surface such as
a simple flap 24 is shown. As illustrated, the flap 24 includes a
hinge line 26, which has a control surface hinge moment indicated
by an arrow A. The wing 22 (having chord length 32) can be
contaminated, for example, with ice or other contaminants, such as
surface roughness, heavy rain, damage due to bird strikes, etc.
Dimensionally, the flap 24 includes a control surface area 30 and a
control surface chord length 33 (from the leading edge of the flap
near hinge line 26 to the trailing edge of the flap), best seen in
FIG. 3. The measurements of the control surface area 30 and the
control surface chord length 33 are preferably constant values that
can be stored for use by the processor 14.
[0031] Nonlimiting examples of a processor 14 include a suitable
configured computer (including as part of or separate from control
systems for an aircraft), a CPU, a suitably programmed chip (e.g.,
ASIC) or board, etc. The processor 14 can be any suitable processor
for analyzing the data according to methods of the claimed
invention, and can be controlled using instructions stored within
hardware, firmware (including hardware of firmware of the processor
or elsewhere), or stored as software instructions on a
non-transitory, tangible medium for reading and executing by the
processor. The processor may be coupled to the sensor or sensors 12
wired or wirelessly using methods and devices known to those of
ordinary skill in the art.
[0032] The sensor (or sensors) 12 is preferably mounted within the
flap 24. If internal mounting is not possible, the sensor 12 can be
externally mounted and faired such that no flowfield unsteadiness
is created that significantly affects the flap hinge moment. Also
preferably stored for use by the processor 14 is information
sufficient to calculate the dynamic pressure, i.e., the kinetic
energy of the surrounding air. The dynamic pressure can be
calculated by taking one-half of the air density times the velocity
of the aircraft squared, and accordingly can be calculated by the
processor 14 based upon a measured air speed. The measured air
speed may be provided by the processor 14, for instance, by
conventional flight systems used to detect air speed.
[0033] In instances of stall for both clean aircraft and
contaminated aircraft, such as (for example only) due to a high ice
ridge formation on the aircraft wing 22, a loss of lift and the
potential for a loss of aircraft controllability exist. Thus, it is
desirable for the sensor system 10 to be able to predict impending
problems before they occur, to give the user ample time to react
and alter the control system.
[0034] A preferred method and system uses a prediction calculation
that is consistent across the widest range of environmental
conditions, such as but not limited to icing, surface roughness,
damage from bird strikes, heavy rain, etc. Example systems and
methods detect changes in the aerodynamics of the section and
provide a warning as to the reduced margins. Current, real-time
data are preferably used, without a priori knowledge of the state
of the section, aircraft, or past events, though it is also
contemplated that certain a priori knowledge could be used. Example
systems and methods can account for changes in the aerodynamics of
the section as a result of physical changes to the airfoil that can
happen either over time, such as with an icing encounter, or
instantaneously, such as a bird strike. A warning buffer in example
embodiments can be provided to the user approximately (that is,
within .+-.0.7 degrees) within a set number of degrees
angle-of-attack, .alpha., prior to stall.
[0035] FIG. 4 shows an example method for predicting airfoil stall
for an aircraft according to an embodiment of the present
invention. The sensor 12, or other suitably located and configured
sensor or sensors, senses the hinge moment, indicated by arrow A in
FIG. 2, about the control surface hinge line 26 over time (step 40)
and generates a plurality of measurements. Each measurement is
generated from an unsteady control surface hinge moment signal that
represents the control surface hinge moment during the time of
acquisition by the processor 14. Data concerning the control
surface hinge moment, i.e., the unsteady control surface hinge
moment signal, is communicated (e.g., exported) to the processor 14
over some period of time (step 42), producing a time series of
unsteady data embodied in unsteady control surface hinge moment
data. These unsteady, time-dependent data are time-averaged to
produce the steady hinge moment response.
[0036] The unsteady hinge moment data is preferably
non-dimensionalized by dividing the hinge moment data by known data
and measurements from aircraft sensors, such as the control surface
area 30, the control chord length 33, and the dynamic pressure,
which are stored for use by the processor 14 (step 44), to
determine a (control surface) hinge moment coefficient, C.sub.h
(step 46). The steady hinge moment coefficients ( C.sub.h); i.e.,
the non-dimensionalized, time-averaged control surface hinge moment
signals, are obtained by time-averaging the unsteady hinge moment
coefficients from step 46. Alternatively, the unsteady hinge moment
data could be averaged and then non-dimensionalized to obtain a
steady hinge moment coefficient.
[0037] Using the resulting steady hinge moment coefficient and
unsteady (time-dependent) hinge moment coefficients, estimates of
the level of unsteadiness in the hinge moment signal can be
determined. In example methods, the unsteady hinge moment signal
over the period of time is filtered in the processor 14 to
minimize, primarily, the influence of structural frequencies
present in the signal (step 48). Such structural frequencies
include frequencies capable of influencing force or moment
measurements acting on the integrated span of the control surface,
e.g., hinge moment measurements by the sensor 12. This removes the
structural unsteady content that could mask the aerodynamic
unsteady content. A nonlimiting example filtering method estimates
structural frequencies by exciting a wind tunnel model wind-off and
observing the power spectrum output of the hinge moment balance.
These estimated structural frequencies are used to determine a
suitable filter, e.g., a low-pass filter, through which the
unsteady hinge moment signal, e.g., unsteady control surface hinge
moment coefficient, C.sub.h, is filtered. Other example filtering
techniques include, but are not limited to, bandstop filtering and
wavelet based denoising.
[0038] The filtered unsteady control surface hinge moment
coefficient, C.sub.h, over time is processed according to
embodiments of the present invention to predict airfoil stall and
to provide a warning of stall a set number of degrees
angle-of-attack prior to stall. Particularly, the filtered unsteady
hinge moment coefficient, represented by C.sub.h, is processed
(step 50) through one or, preferably, a combination of various
stall warning detection functions (which can be programmed in the
processor 14, for example) for predicting stall at a preset number
of degrees angle-of-attack prior to stall. In a nonlimiting example
system and method, stall warning detection functions are provided
based upon the unsteady hinge moment produced by an aerodynamic
control surface. Generally, each of the stall warning detection
functions are configured to receive the filtered unsteady hinge
moment signal, e.g., filtered control surface hinge moment
coefficient C.sub.h, as an input, and generate an output that is
compared to a threshold to identify the angle-of-attack as being
approximately within a certain number of degrees of airfoil stall.
Preferably, the stall warning detection function can identify this
condition over background noise, and for both clean and for
contaminated lifting surfaces of various types. Selection of
preferable stall warning detection functions can account for
multiple flap angles and various Reynolds numbers.
[0039] It is also preferred that the filtered unsteady hinge moment
signal is input to each of multiple stall warning detection
functions, and the results of the individual detection functions
are combined (step 52), e.g., averaged, to produce a combined
warning In an example embodiment, for multiple detection functions,
the outputs of each individual detection function can be compared
to a threshold to create a local angle-of-attack margin, and the
margins of each method can be averaged to obtain the final warning
boundary. Use of multiple stall warning detection functions helps
minimize the effect of outlying results from any particular
function. If multiple sensors 12 are used for a single control
surface, the outputs of the multiple detector functions could be
combined, e.g., averaged, or compared to provide redundancy into
the stall warning system.
[0040] Two nonlimiting example types of stall warning detection
functions are provided according to embodiments of the present
invention. One example method and system includes a combination of
a moment, derivative, and spectrum based approach (and in some
embodiments, time normalized energy), while other example methods
and systems include a wavelet-based approach. Both example types of
methods can be successful for certain types of airfoil sections.
Those of ordinary skill in the art will appreciate that other stall
warning detection functions and wavelets are possible for use in
processing according to other embodiments of the invention.
[0041] If the output (or combined output) generated by the
processing (step 50, and step 52 if combined output) exceeds the
threshold (step 54), which occurs at an angle-of-attack that is
prior to an angle-of-attack for airfoil stall, the processor 14
produces an output signal (step 56), which may be sent to the
display device 16, alarm, or information system, for example. In a
preferred embodiment, the display device 16 then alerts the user
(step 58) so that corrective action, e.g., adjustments to the
controls, can be made, avoiding a possible accident. Based on the
result from the employed detection function(s), the output signal
(step 56) can be a warning signal that is sent to the display
device 16. It is also contemplated that the signal could also be
input into other aircraft information systems, where the signal
could be integrated with other information. Upon receiving a
signal, the display device 16 can alert the user (step 58) by
displaying a warning signal to the operator. Warnings such as a
flashing light, alarm, screen display (e.g., a display containing
words such as WARNING and particular conditions), vibration
feedback, or other suitable alarm are contemplated.
[0042] For purposes of illustration of certain features of example
embodiments, hinge moment data are obtained from wind tunnel tests
on two different example airfoil sections, a NACA 3415 and a NACA
23012. Data from the NACA 3415 wind tunnel test are first used to
develop a nonlimiting example predictive detection function. The
NACA 23012 wind tunnel test data is then used to develop an example
wavelet based detection method.
[0043] In experiments demonstrating nonlimiting example methods
according to the present invention, experimental hinge moment data
from the NACA 3415 test are used to develop a predictive stall
warning function. This example function is based on the unsteady
hinge moment signal from a simple flap on the airfoil. The example
method and system developed based on the NACA 3415 test data uses a
combination of three separate functions to provide a warning at a
preset number of degrees angle-of-attack prior to stall. These
three functions are based on the unsteady hinge moment time trace,
which is represented in particular example embodiments by the
filtered unsteady control surface hinge moment coefficient C.sub.h,
though it is also contemplated to use hinge moment signals without
non-dimensionalizing them.
[0044] The first example function developed calculates the 4th
order moment about the mean of the unsteady hinge moment signal.
The 4th order moment is often termed the kurtosis of the signal and
is basically a measure of the spread of the signal from the mean (
C.sub.h). The second example function developed is a time
derivative based function of the unsteady hinge moment signal. The
example function calculates the square of the first and second
derivative of the hinge moment signal, takes a sum of those values,
and then an average over the time trace. The example third function
integrates the power spectrum (PSD) of the hinge moment time
history over a given frequency interval. This approach essentially
provides the energy content of the signal over a given frequency
range. The three separate example detection functions are provided
below:
Moment = 1 n i = 0 n - 1 ( C h - C _ h ) 4 1 st Function Derivative
= 1 n i = 0 n - 1 ( C h 2 t + 2 C h 2 t 2 ) 2 2 nd Function
Spectrum = .intg. 0 Hz 50 Hz PSD ( C h ) f 3 rd Function
##EQU00001##
[0045] Prior to calculating the three example detection functions,
the unsteady hinge moment signal coefficient is filtered, e.g.,
low-pass filtered, as explained above, to remove any (or a
substantial amount of) structural frequencies present in the
signal. The structural frequencies are estimated during an example
test by exciting the model wind-off and observing the power
spectrum output of the hinge moment balance. These structural
frequencies for the NACA 3415 model were on the order of 200-500
Hz. The example low-pass filter cut-off frequency was set at 50
Hz.
[0046] A plot showing the output of the three example detector
functions for the clean NACA 3415 model as a function of
angle-of-attack at Re=1.8.times.10.sup.6 and 0 degree flap angle is
shown in FIG. 5. Also included in the figure are the lift curve and
a line denoting .alpha..sub.stall. As shown in FIG. 5, each of the
detector functions produces a relatively smooth output, which
significantly increases in magnitude several degrees prior to
stall. Above .alpha.=0.degree., the functions provide a monotonic
increase in level with increasing .alpha. until stall. In addition
to increasing magnitudes as stall is approached, the slope of each
of the detector function outputs is also shown to increase. Using a
threshold based approach, the three example detector functions
appear to provide sufficient output and a large enough
signal-to-noise ratio to be used as accurate predictive indicators
of stall several degrees angle-of-attack prior to stall.
[0047] In order for the detection functions to be useful for
predicting stall, the example functions should provide a consistent
output across the widest range of environmental conditions,
including icing, surface contamination such as roughness or heavy
rain, surface damage such as bird strikes, etc. If the output is
not consistent across these (or other) different hazards, a simple
threshold based approach (for example) may produce inconsistent
results dependent upon the hazard. A plot showing the output of the
three example detector functions for the clean NACA 3415 model and
the model with all six tested simulated contaminants as a function
of angle-of-attack prior to stall (.alpha.-.alpha..sub.stall) at
Re=1.8.times.10.sup.6, flap=0.degree. is shown in FIGS. 6A-6C,
where FIG. 6A indicates the moment function output, FIG. 6B
indicates the derivative function output, and FIG. 6C indicates the
spectrum function output.
[0048] From FIGS. 6A-6C, the output for each of the three separate
detector functions for the clean model and the model with all six
simulated contaminants collapse onto a single curve with the
exception of the simulated upper surface damage case. As a result,
a simple threshold can be set for each of the detector functions
based on a warning boundary a set number of degrees prior to
.alpha..sub.stall. For the example data shown, there appears to be
enough signal in the detector function outputs to provide a
boundary warning range of 1.degree. to 4.degree. prior to actual
stall. In the occurrence of an inconsistency between one detector
function and the other two detector functions, the difference of
stall margin could be used to determine or deduce whether or not an
error has occurred in one of the detector functions, since the
three example detector functions estimate the stall margin with
methods unique to that detector function. If the deviation between
the stall margins provided by one of the detector functions and the
average of the other two detector functions is too large, a case
system could be implemented to remove the outlying detector
function output from the averaging process.
[0049] For the data shown in FIGS. 6A-6C, for example purposes, a
threshold level is chosen to provide a warning 2.degree. prior to
stall. This single threshold (for each detector function) would
appear to provide a relatively accurate warning boundary for all
the cases shown, with the exception of the simulated upper surface
damage case. The upper surface damage case does not collapse well
due to its isolated 3D nature on the model surface. While premature
separation may have occurred in the spanwise region of the
protuberances, other spanwise regions of the model would not have
experienced the perturbation from the simulated damage. For the
current set of data used for these examples, a floor-mounted force
and moment balance was used to obtain the lift and quarter-chord
pitching moment measurements. Since the sectional lift was
calculated from the wind tunnel floor balance, the entire span of
the model was included in the example measurement. As a result, the
overall loss in lift for the upper surface damage case is
relatively small, and .alpha..sub.stall is relatively
unchanged.
[0050] Again, this example set-up mimics what would be observed on
an aircraft wing where the effect of an isolated structural
incident would be integrated over the entire control surface. This
fact, coupled with the relatively close chordwise proximity of the
simulated damage to the flap, produces an elevated detector
function output that does not collapse like the other simulated
contaminants While the single threshold approach would produce a
premature boundary warning for this example case, the example
system would alert the user to a change in the aerodynamics of the
configuration, and the location of the issue. Overall, however, the
example detector functions developed work well across all but one
of the contaminants tested.
[0051] The example threshold level is observed to be a function of
flap angle. The threshold level as a function of flap deflection
for a stall warning boundary of 2.degree. for each of the three
example detector functions at Re=1.8.times.10.sup.6 is shown in
FIG. 7. In order to give a correct representation of the magnitude
of the threshold level change as a function of flap angle, the
vertical scales for the threshold levels shown in FIG. 7 are
identical to those shown in FIGS. 6A-6C and FIG. 5. From FIG. 7,
the example threshold level is shown to be a moderate function of
flap angle, with the threshold level generally increasing with
increasing positive flap deflection.
[0052] In an example hinge moment monitoring system, the individual
stall boundary warnings produced by the three separate example
detection functions are averaged to provide a single stall boundary
warning The averaging of the three separate functions provides a
level of redundancy in the calculation to minimize the influence of
outliers in the data that might appear in one of the functions. A
standard deviation calculation between the three different methods
computed in real-time could also be used as a measure of the
confidence in the stall boundary warning prediction.
[0053] Based on the threshold levels shown in FIG. 7 for an
envelope boundary warning of 2.degree., stall warning boundaries
were generated for the clean NACA 3415 model, and the model with
all six of the example contaminants tested at Re=1.8.times.10.sup.6
for the five flap deflections tested. The example predicted stall
warning boundaries as a function of flap angle are shown in FIG.
8.
[0054] The results shown in FIG. 8 indicate the magnitude of the
angle-of-attack value prior to stall produced by the average of the
three stall warning prediction functions. A value of 2.degree.
would indicate a perfect correlation to the set warning boundary. A
value above 2.degree. indicates the example detection function
produced a boundary warning at an angle-of-attack lower than the
set 2.degree. prior to stall, with a value below 2.degree.
indicating a boundary warning closer to stall than the set value.
As shown in FIG. 8, for the majority of the cases the example
detection function produces a warning within .+-.0.7.degree. of the
set boundary value.
[0055] The two cases which fall outside of this range are the rime
ice and upper surface damage cases. The results for the upper
surface damage case are as expected, based on the results shown in
FIGS. 6A-6C, as described above. The second outlying data set is
that of the simulated rime ice case. The simulated rime ice case
produces a warning approximately 2.degree. prior to the example set
2.degree. warning mark (4.degree. prior to stall). This premature
warning is due to the rime case producing a larger unsteadiness in
the hinge moment output than the other example cases.
[0056] Overall, across the wide range of simulated contaminants
tested, the example functions used for stall warning prediction
functioned well. All of the warnings produced were prior to actual
stall. The largest outliers produced a conservative error, prior to
the set warning boundary.
[0057] In addition to the three example detection functions shown,
an additional type of detection function can be provided in
particular embodiments of the invention. This additional example
type of detection addresses potential concerns about the
reliability of the derivative based detection function in a noisy
flight environment, even though the data are preferably filtered
(e.g., low-pass filtered) before being operated upon. An example
additional function determines time normalized energy of the hinge
moment signal. This example function can operate in the same
fashion as the moment, spectrum, and derivative functions in
question.
[0058] The experimental data and results presented in these
nonlimiting examples has been for a single Reynolds number,
Re=1.8.times.10.sup.6. Data were also obtained in other examples at
Re=1.0.times.10.sup.6. The lower Reynolds number data closely
matches the higher Re data. At these low Reynolds numbers, the
differences between these two cases are primarily laminar/turbulent
transition based. For vehicles using the example hinge moment
detection system, minimum Reynolds numbers would most likely be in
the 6 to 8 million range where transition is most likely very near
the leading edge. For the example cases run, the lower Reynolds
number results closely mimic the Re=1.8.times.10.sup.6 results. The
threshold levels for the Re=1.0.times.10.sup.6 results are slightly
lower than those obtained for the Re=1.8.times.10.sup.6 cases, with
the overall results being similar At the higher Reynolds numbers
experienced on actual flight vehicles, where transition is more
closely fixed near the leading edge, it is conceivable that there
may be no Reynolds number effect due to the fact that the hinge
moment data are reduced to coefficient form (dynamic pressure taken
into account).
[0059] Another set of example detection functions were developed
using data from the NACA 23012 model. These functions utilize
wavelet based analyses, according to another example embodiment of
the present invention. Theoretically, the unsteady hinge moment
signal, e.g., the unsteady hinge moment coefficient, can be thought
of as two convolved signals: a mean signal based on the steady
pressure distribution and steady forcing from processes such as the
Karman street shed from the trailing-edge, and an unsteady signal
based on eddies shed from separation bubbles, separated shear
layers, and boundary layers approaching incipient separation. In
order to isolate the unsteady content of the signal generated by
the separation, the signal might be de-convolved, or the mean and
steady forcing filtered out. A wavelet based denoising technique is
used in example embodiments to attempt to isolate the unsteady
separation dominated hinge moment signal.
[0060] Unlike a continuous periodic function, such as a sine or
cosine wave, a wavelet is a wave-like function whose amplitude
starts and ends at zero. Wavelets are generally designed to have
specific properties and shapes, depending upon their use. They are
commonly used for advanced signal processing and filtering
techniques. A wavelet with a given shape and properties can be
convolved with a signal. If the unknown signal contains information
similar to the wavelet, the wavelet will resonate, much like a
tuning fork resonates with sound waves of its specific tuning
frequency. As a result, wavelet analysis can be used according to
embodiments of the present invention to capture the transient
features of a signal.
[0061] One example technique is called wavelet denoising. In
denoising, a given signal is essentially filtered to remove
unwanted information and highlight certain aspects of the signal.
Wavelet denoising is done in three primary steps: 1) a linear
forward wavelet transform is performed; 2) a nonlinear denoising is
performed, where the transformed signal is thresholded in the
waveform domain using any different number of thresholding
techniques; and 3) finally, a linear inverse wavelet transform is
performed to retrieve the denoised signal. In order to perform the
wavelet denoising in example embodiments a "mother" wavelet is
chosen. The mother wavelet contains the signal characteristics of
interest. Generally, the mother, or primary, wavelet is developed
based upon the transient features one desires to highlight.
[0062] In an example method, several wavelet denoising routines
present in the National Instruments LabVIEW acquisition and
analysis environment were used to determine the viability of using
wavelets to isolate the unsteady separation content of the hinge
moment signal. In the absence of a mother, or primary, wavelet
specifically developed for the unsteady hinge moment signal,
various primary wavelets available in the LabVIEW denoising
routines were tested. Wavelets were tested by processing the
unsteady hinge moment signal at several angles-of-attack well below
stall, then at the set warning boundary angle-of-attack, and post
stall. Wavelets were chosen that provided relatively no signal
output prior to the warning boundary angle-of-attack, yet produced
significant output at the warning boundary angle-of-attack. As a
nonlimiting example, for the NACA 23012 data, these wavelets
included the Sym2, Haar, and Coif2 wavelets. Images of the three
wavelet functions are shown in FIGS. 9A, 9B, and 9C
respectively.
[0063] Much like the three different example detector functions
developed for the NACA 3415 data, the three example primary
wavelets were used to develop a stall warning prediction. The
example function passes the unsteady hinge moment signal through
the wavelet denoising transform. The absolute value of the output
from the transform is then passed through a baselining process,
where any signal above zero is converted to a nominal value. The
total percentage of the signal above zero is then calculated. A
threshold based on the total percentage value of the signal above
zero is then used to determine the warning boundary. As with the
NACA 3415 data, before the data were processed using the wavelet
transforms, the data were low-pass filtered at 50 Hz to minimize
the effect of structural frequencies. A plot showing the clean NACA
23012 lift curve is shown in FIG. 10A, and outputs from the Haar
based wavelet transform for selected points 60, 62, 64, 66 are
shown in FIGS. 10B, 10C, 10D, and 10E respectively.
[0064] Also shown in FIG. 10F is the graph showing the percentage
of the signal above the baseline zero value. From FIG. 10F, at low
angles-of-attack, there is only minor, scattered response present
in the example wavelet transform output. At moderate angles of
attack (.alpha..apprxeq.9.degree.), no response is present in the
signal. At the prescribed warning boundary of 2.degree. prior to
stall (.alpha..apprxeq.13.9.degree.), the example wavelet transform
produces significant output. Post stall
(.alpha..apprxeq.16.2.degree.), the magnitude of the output has
reduced significantly, but signal is still present. The example
wavelet denoising transform appears to be extracting the separation
based content of the hinge moment signal. While the magnitude of
the output greatly decreases past stall, the signal is still
present. Using the approach of calculating the percentage of the
signal above a zero baseline allows a normalization of the signal
output. FIG. 10F, showing the percentage of the signal above the
baseline zero value, shows very little behavior below stall, and
begins to grow rapidly around the 2.degree. warning boundary. A
threshold is then chosen based on the desired warning boundary.
Warning boundaries calculated using the three different example
primary wavelets for a 2.degree. pre-stall boundary for the clean
NACA 23012 model and the model with the six simulated contaminants
are shown in FIG. 11, along with the average of the three example
wavelet prediction methods.
[0065] As shown in FIG. 11, the example wavelet based prediction
method functions well for the NACA 23012 model with no flap
deflection. The average boundary prediction error produced by three
example wavelet functions is under .+-.0.5.degree.. The function
also worked well for the simulated damage cases. Only one
significant outlier point exists for the Sym2 wavelet prediction of
the simulated leading-edge damage case. While the example functions
and methodologies developed for the NACA 23012 section with zero
flap angle appear to function well, the results for the flap
deflected section tends to under predict the stall angle by several
degrees and are noisier. To more accurately extend the analysis to
the other flap deflections, a custom wavelet can be developed based
upon the hinge moment signal. In order to develop a custom wavelet,
aerodynamic forcing frequencies may need to be determined so that
they could be accurately extracted using the example transform
based approach.
[0066] A significant application of the example wavelet method is
that different wavelets can be developed for different types of
stalling characteristics or hazards. Results from any section might
also be filtered using multiple wavelets. If a given wavelet is
tuned to a certain type of stalling characteristic, the output of
that wavelet transform should be able to identify that stalling
characteristic, where the other wavelets should produce a null
output. An example multiple wavelet method could allow a family of
wavelets to be developed, which would allow the example wavelet
detection method to be applicable across a very wide range of
sections with very different stalling characteristics and
aerodynamic hazards.
[0067] Overall, the example predictive stall warning detection
functions developed based on the unsteady hinge moment signal
appear to provide various features and benefits. For example, the
three example detection functions developed for the NACA 3415
results functioned well across the wide range of simulated
contaminants tested. For the majority of the cases, the detection
function produces a warning within .+-.0.7.degree. of the set
boundary value. The averaging of the three separate example
functions provides a level of redundancy in the calculation, and
can also be used as a measure of the confidence in the example
stall boundary warning prediction. Additionally, there appears to
be sufficient signal in example methods to extend the stall warning
boundary further, e.g., out to 3.degree.-4.degree. prior to stall.
Although not used in this experimental analysis, the example fourth
detection function can be developed and used based on the time
normalized energy of the signal, as explained above, to address
concerns of using the derivative based approach on noisier
flight-based hinge moment measurements.
[0068] Much like the example predictive stall warning detection
functions, three different primary wavelet based approaches were
used in another example embodiment to generate stall warning
boundaries, and the results were averaged to produce a single
warning The results produced for the NACA 23012 with and without
the simulated contaminants at Re=1.8.times.10.sup.6 and no flap
deflection produced beneficial results. The average boundary
prediction error produced by the three example wavelet functions
was under .+-.0.5.degree.. While the example wavelet based
prediction function was shown to function well for some cases,
e.g., undeflected flap case, to accurately extend the wavelet based
analysis to the other flap deflections a custom wavelet, or family
of wavelets based upon the hinge moment signal, may be provided.
This may allow the wavelet based detection method to be applicable
across a very wide range of sections with very different stalling
characteristics and aerodynamic hazards.
[0069] While example methods are described with respect to a 2D
environment, it is also contemplated that methods can be extended
to a 3D finite wing with multiple control surfaces to function in a
more complex environment. Also, though particular custom wavelets
can be used, it is also contemplated that a uniform envelope
prediction system could be provided according to embodiments of the
present invention to function across multiple platforms based on
different sections.
[0070] Nonlimiting example applications of the present invention
are regional and commercial aircraft manufacturing, and vehicle
aerodynamic health monitoring system manufacturing.
[0071] While various embodiments of the present invention have been
shown and described, it should be understood that other
modifications, substitutions, and alternatives are apparent to one
of ordinary skill in the art. Such modifications, substitutions,
and alternatives can be made without departing from the spirit and
scope of the invention, which should be determined from the
appended claims.
[0072] Various features of the invention are set forth in the
appended claims.
* * * * *